<p>Offers New Insight on Uncertainty ModellingFocused on major research relative to spatial information, Uncertainty Modelling and Quality Control for Spatial Data introduces methods for managing uncertainties-such as data of questionable quality-in geographic information science (GIS) applications.
Uncertainty modelling and quality control for spatial data
✍ Scribed by Stein, Alfred; Wenzhong, Shi; Wu, Bo
- Publisher
- CRC Press
- Year
- 2016
- Tongue
- English
- Leaves
- 312
- Category
- Library
No coin nor oath required. For personal study only.
✦ Table of Contents
Content: UNCERTAINTY MODELLING AND QUALITY CONTROLUncertainty-Related Research Issues in Spatial AnalysisDaniel A. Griffith, David W. Wong, and Yongwan ChunSpatial Statistical Solutions in Spatial Data Quality to Answer Agricultural Demands Based on Satellite ObservationsAlfred Stein, Muhammad Imran, and Milad MahourEliminating Systematic Error in Analytical Results of GIS ApplicationsN. Chrisman and J.-F. GirresFunction Workflow Design for Geographic Information System: A Data Quality PerspectiveJ.-H. Hong and M.-L. HuangUNCERTAINTIES IN MULTIDIMENSIONAL AND MULTISCALE DATA INTEGRATIONData Quality in the Integration and Analysis of Data from Multiple Sources: Some Research ChallengesJ. Harding, L. Diamond, J. Goodwin, G. Hart, D. Holland, M. Pendlington, and A. RadburnQuality Management of Reference GeoinformationA. Jakobsson, A. Hopfstock, M. Beare, and R. PatruccoA New Approach of Imprecision Management in Qualitative Data WarehouseF. Amanzougarene, M. Chachoua, and K. ZeitouniQuality Assessment in River Network Generalisation by Preserving the Drainage PatternZhang and E. GuilbertQUALITY CONTROL FOR SPATIAL PRODUCTSQuality Control of DLG and Map ProductsPei Wang, Zhiyong Lv, Libin Zhao, and Xincheng GuoVGI for Land Administration: A Quality PerspectiveGerhard Navratil and Andrew U. FrankQualitative and Quantitative Comparative Analysis of the Relationship between Sampling Density and DEM Error by Bilinear and Bicubic Interpolation MethodsWenzhong Shi, Bin Wang, and Eryong LiuAutomatic Method of Inspection for Deformation in Digital Aerial Imagery Based on Statistical CharacteristicsYaohua Yi, Yuan Yuan, Hai Su, and Mingjing MiaoComparison of Point Matching Techniques for Road Network MatchingA. Hackeloeer, K. Klasing, J. M. Krisp, and L. MengUNCERTAINTIES IN SPATIAL DATA MININGTowards a Collaborative Knowledge Discovery System for Enriching Semantic Information about Risks of Geospatial Data MisuseJ. Grira, Y. Bedard, and S. RocheUncertainty Management in Seismic Vulnerability Assessment Using Granular Computing Based on Neighborhood SystemsF. Khamespanah, M.R. Delavar, and M. ZareIncreasing the Accuracy of Classification Based on Ant Colony AlgorithmMing Yu, Chen-Yan Dai, and Zhi-Lin Li
✦ Subjects
Математика;Теория вероятностей и математическая статистика;Математическая статистика;Прикладная математическая статистика;Пространственная статистика;
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When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial dat
<p><P>This volume is dedicated to the memory of Professor Ashley Morris who passed away some two years ago. Ashley was a close friend of all of us, the editors of this volume, and was also a Ph.D. student of one of us. We all had a chance to not only fully appreciate, and be inspired by his contribu